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Purpose Childhood epilepsies have a strong genetic contribution, but the disease trajectory for many genetic etiologies remains unknown. Electronic medical record (EMR) data potentially allow for the analysis of longitudinal clinical information but this has not yet been explored. Methods We analyzed provider-entered neurological diagnoses made at 62,104 patient encounters from 658 individuals with known or presumed genetic epilepsies. To harmonize clinical terminology, we mapped clinical descriptors to Human Phenotype Ontology (HPO) terms and inferred higher-level phenotypic concepts. We then binned the resulting 286,085 HPO terms to 100 3-month time intervals and assessed gene–phenotype associations at each interval. Results We analyzed a median follow-up of 6.9 years per patient and a cumulative 3251 patient years. Correcting for multiple testing, we identified significant associations between “Status epilepticus” with SCN1A at 1.0 years, “Severe intellectual disability” with PURA at 9.75 years, and “Infantile spasms” and “Epileptic spasms” with STXBP1 at 0.5 years. The identified associations reflect known clinical features of these conditions, and manual chart review excluded provider bias. Conclusion Some aspects of the longitudinal disease histories can be reconstructed through EMR data and reveal significant gene–phenotype associations, even within closely related conditions. Gene-specific EMR footprints may enable outcome studies and clinical decision support.

Purpose TANGO2-related disorders were first described in 2016 and prior to this publication, only 15 individuals with TANGO2-related disorder were described in the literature. Primary features include metabolic crisis with rhabdomyolysis, encephalopathy, intellectual disability, seizures, and cardiac arrhythmias. We assess whether genotype and phenotype of TANGO2-related disorder has expanded since the initial discovery and determine the efficacy of exome sequencing (ES) as a diagnostic tool for detecting variants. Methods We present a series of 14 individuals from 11 unrelated families with complex medical and developmental histories, in whom ES or microarray identified compound heterozygous or homozygous variants in TANGO2. Results The initial presentation of patients with TANGO2-related disorders can be variable, including primarily neurological presentations. We expand the phenotype and genotype for TANGO2, highlighting the variability of the disorder. Conclusion TANGO2-related disorders can have a more diverse clinical presentation than previously anticipated. We illustrate the utility of routine ES data reanalysis whereby discovery of novel disease genes can lead to a diagnosis in previously unsolved cases and the need for additional copy-number variation analysis when ES is performed.

Purpose: Diagnostic exome sequencing (DES) is now a commonly ordered test for individuals with undiagnosed genetic disorders. In addition to providing a diagnosis for characterized diseases, exome sequencing has the capacity to uncover novel candidate genes for disease. Methods: Family-based DES included analysis of both characterized and novel genetic etiologies. To evaluate candidate genes for disease in the clinical setting, we developed a systematic, rule-based classification schema. Results: Testing identified a candidate gene among 7.7% (72/934) of patients referred for DES; 37 (4.0%) and 35 (3.7%) of the genes received evidence scores of “candidate” and “suspected candidate,” respectively. A total of 71 independent candidate genes were reported among the 72 patients, and 38% (27/71) were subsequently corroborated in the peer-reviewed literature. This rate of corroboration increased to 51.9% (27/52) among patients whose gene was reported at least 12 months previously. Conclusions: Herein, we provide transparent, comprehensive, and standardized scoring criteria for the clinical reporting of candidate genes. These results demonstrate that DES is an integral tool for genetic diagnosis, especially for elucidating the molecular basis for both characterized and novel candidate genetic etiologies. Gene discoveries also advance the understanding of normal human biology and more common diseases. Genet Med 19 2, 224–235.